The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLVI-4/W1-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W1-2021, 77–83, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W1-2021-77-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W1-2021, 77–83, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W1-2021-77-2021

  03 Sep 2021

03 Sep 2021

A PROJECTION-BASED RECONSTRUCTION ALGORITHM FOR 3D MODELING OF BRIDGE STRUCTURES FROM DRONE-BASED POINT CLOUD

M. Mehranfar1, H. Arefi1,2, and F. Alidoost3 M. Mehranfar et al.
  • 1School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran
  • 2School of Technology, Department of Geoinformatics and Surveying, Mainz University of Applied Sciences, Germany
  • 3Faculty of Geomatics, Computer Science and Mathematics, Stuttgart University of Applied Sciences, Germany

Keywords: Bridge structures, 3D reconstruction, Point cloud, Fuzzy c-means, CAD

Abstract. This paper presents a projection-based method for 3D bridge modeling using dense point clouds generated from drone-based images. The proposed workflow consists of hierarchical steps including point cloud segmentation, modeling of individual elements, and merging of individual models to generate the final 3D model. First, a fuzzy clustering algorithm including the height values and geometrical-spectral features is employed to segment the input point cloud into the main bridge elements. In the next step, a 2D projection-based reconstruction technique is developed to generate a 2D model for each element. Next, the 3D models are reconstructed by extruding the 2D models orthogonally to the projection plane. Finally, the reconstruction process is completed by merging individual 3D models and forming an integrated 3D model of the bridge structure in a CAD format. The results demonstrate the effectiveness of the proposed method to generate 3D models automatically with a median error of about 0.025 m between the elements’ dimensions in the reference and reconstructed models for two different bridge datasets.